University of Warsaw Lagrangian Cloud Model (UWLCM) 2.0: Adaptation of a mixed Eulerian-Lagrangian numerical model for heterogeneous computing clusters

A numerical cloud model with Lagrangian particles coupled to an Eulerian flow is adapted for distributed memory systems. Eulerian and Lagrangian calculations can be done in parallell on CPUs and GPUs, respectively. Scaling efficiency and the amount of parallelization of CPU and GPU calculations both exceed 50 % for up to 40 nodes. A sophisticated Lagrangian microphysics model slows down simulation by only 50 % compared to a simplistic bulk microphysics model, thanks to the use of GPUs. Overhead of communications between cluster nodes is mostly related to the pressure solver. Presented method of adaptation for computing clusters can be used in any numerical model with Lagrangian particles coupled to an Eulerian fluid flow.

Impacts of a Storm Merger on the 24 May 2011 El Reno, Oklahoma, Tornadic Supercell

On 24 May 2011, a tornadic supercell (the El Reno, Oklahoma, storm) produced tornadoes rated as category 3 and 5 events on the enhanced Fujita scale (EF3 and EF5, respectively) during a severe weather outbreak. The transition (“handoff”) between the two tornadoes occurred as the El Reno storm merged with a weaker, ancillary storm. To examine the impacts of the merger on the dynamics of these storms, a series of three-dimensional cloud-scale analyses are created by assimilating 1-min volumetric observations from the National Weather Radar Testbed’s phased array radar into a numerical cloud model using the local ensemble transform Kalman filter technique. The El Reno storm, its updrafts, and vortices in the analyzed fields are objectively identified, and the changes in these objects before, during, and after the merger are examined. It is found that the merger did not cause the tornado handoff, which preceded the updraft merger by about 5 min. Instead, the handoff likely resulted from midlevel mesocyclone occlusion, in which the midlevel mesocyclone split and a portion is shed rearward with respect to storm motion. During the merger process, the midlevel mesocyclone and updraft structure in the El Reno storm became relatively disorganized. New updraft pulses that formed above colliding outflow boundaries between the two storms tilted environmental vorticity from low levels to generate an additional midlevel vortex that later merged with the El Reno storm’s midlevel mesocyclone. Once the ~10-min merger process was complete, the El Reno storm and its mesocyclone rapidly reintensified, as access to buoyant inflow sector air was restored.

Aerosols' influence on the interplay between condensation, evaporation and rain in warm cumulus cloud

A numerical cloud model is used to study the influence of aerosol on the microphysics and dynamics of moderate-sized, coastal, convective clouds that develop under the same meteorological conditions. The results show that polluted convective clouds start their precipitation later and precipitate less than clean clouds but produce larger rain drops. The evaporation process is more significant at the margins of the polluted clouds (compared to the clean cloud) due to a higher drop surface area to volume ratio and it is mostly from small drops. It was found that the formation of larger raindrops in the polluted cloud is due to a more efficient collection process.

Aerosols' influence on the interplay between condensation, evaporation and rain in warm cumulus cloud

A numerical cloud model is used to study the influence of aerosol on the microphysics and dynamics of moderate-sized, coastal, convective clouds that develop under the same meteorological conditions. The results show that polluted convective clouds start their precipitation later and precipitate less than clean clouds but produce larger rain drops. The evaporation process is more significant at the margins of the polluted clouds (compared to the clean cloud) due to a higher drop surface area to volume ratio and it is mostly from small drops. It was found that the formation of larger raindrops in the polluted cloud is due to a more efficient collection process.

Growth and Decay of Error in a Numerical Cloud Model Due to Small Initial Perturbations and Parameter Changes

The behavior of a numerical cloud model is investigated in terms of its sensitivity to perturbations with two kinds of lateral boundary conditions: 1) with cyclic lateral boundary conditions, the model is sensitive to many aspects of its structure, including a very small potential temperature perturbation at only one grid point, changes in time step, and small changes in parameters such as the autoconversion rate from cloud water to rainwater and the latent heat of vaporization; 2) with prescribed lateral boundary conditions, growth and decay of perturbations are highly dependent on the flow conditions inside the domain. It is shown that under relatively uniform (unidirectional) advection across the domain, the perturbations will decay. On the other hand, convergence, divergence, or, in general, flow patterns with changing directions support error growth. This study shows that it is the flow structure inside the model domain that is important in determining whether the prescribed lateral boundary conditions will result in decaying or growing perturbations. The numerical model is inherently sensitive to initial perturbations, but errors can decay due to advection of information from lateral boundaries across the domain by uniform flow. This result provides one explanation to the reported results in earlier studies showing both error growth and decay.